<Current VICS Traffic Information>
VICS (Vehicle Information and Communication System) which currently provides a car navigation system with a traffic information provision system collects and edits traffic information and transmits traffic congestion information and travel time information representing the time required by way of an FM multiplex broadcast or a beacon.
The current VICS information represents the current traffic information as follows:
Traffic situation is displayed in three stages, congestion (ordinary road: ≦10 km/h; expressway: ≦20 km/h);
heavy traffic (ordinary road: 10-20 km/h; expressway: 20-40 km/h); and light traffic (ordinary road: ≦20 km/h; expressway: ≦40 km/h).
The traffic congestion information representing the traffic congestion is displayed as
“VICS link number+state (congestion/heavy traffic/light traffic/unknown)” in case the entire VICS link (position information identifier) is congested uniformly.
In case only part of the link is congested, the traffic congestion information representing the traffic congestion is displayed as
“VICS link number+congestion head distance (distance from beginning of link)+congestion end (distance from beginning of link)+state (congestion)”
In this case, when the congestion starts from the start end of a link, the head congestion distance is displayed as 0xff. In case different traffic situations coexist in a link, each traffic situation is respectively described in accordance with this method.
The link travel time information representing the travel time of each link is displayed as “VICS link number+travel time”
As prediction information representing the future change trend of traffic situation, an increase/decrease trend graph showing the four states, “increase trend/decrease trend/no change/unknown” is displayed while attached to the current information.
<Transmission of Road Position Independent of VICS Link Number>
VICS traffic information displays traffic information while identifying a road with a link number. The receiving party of this traffic information grasps the traffic situation of the corresponding road on its map based on the link number. The system where the sending party and receiving party shares link numbers and node numbers to identify a position on the map requires introduction or a change in new link numbers and node numbers each time a road is constructed anew or changed. With this, the data on the digital map from each company needs updating so that the maintenance requires huge social costs.
In order to offset these disadvantages, the inventors of the invention proposes, in the Japanese Patent Laid-Open No. 2001-41757, a system where a sending party arbitrarily sets a plurality of nodes on a road shape and transmits a “shape data string” representing the node position by a data string and a receiving party uses the shape data string to perform map matching in order to identify a road on a digital map. A system which compresses data by way of Fourier coefficient approximation to delete the data volume of this shape data string is proposed in the Japanese Patent Laid-Open No. 2002-228467. A system which applies statistical processing on the data to convert the data into data which concentrates around ±0 and then converts the data to variable length encoded data for data compression is proposed in the Japanese Patent Application No. 2001-134318.
The following approach is possible as an approach to correct a shape data using relative positions for display. In case the positions of nodes included in a shape data, cumulative errors occur. The cumulative errors tend to accumulate in case the shape data has a long distance and has a “gentle shape” such as the National Highway 268 and the National Highway 1. In order to prevent this, the shape as a shape data is extracted so that the shape will be temporarily bent by way of a crossing road as shown in thick lines in FIG. 40 and then returned to the main route. In this practice, a “point which characterizes the shape” such as the intersection or a curve with a large curvature is set as a reference node to cancel the cumulative errors. The receiving party compares the distance between reference nodes shown in dotted lines obtained by decoding the received data with the distance between reference nodes of a shape data shown in thick lines thus correcting the relative positions. A reference node specified in a position where cumulative errors can be corrected is hereinafter referred to as a “reference node for correction of relative position”.
With this system, it is possible to transmit a road position without using link numbers or node numbers.
[Patent Document 1]                Japanese Patent Laid-Open No. 2001-41757        
[Patent Document 2]                Japanese Patent Laid-Open No. 2002-228467        
However, the currently provided traffic information has the following problems and cannot support a variety of requests for road information, that is, traffic information in line with general traffic information, information on the areas along the road, and information on the pertinent road.
<Problem 1 of the Current Traffic Information>
In the current traffic information, resolution of information representation is too coarse. The congestion information can be displayed in units of 10 meters concerning the position although the number of traffic information representations is only three, traffic congestion, heavy traffic and light traffic.
Representation of traffic information concerning the link travel time may be made in units of 10 seconds although the position resolution is only “per link” and the minute speed distribution in the link cannot be represented.
This could present the following problem:
As shown in FIG. 41, a person saw the display of the congested section (section where the vehicle speed is 10 km/h or below) and thinking that the time required to get out of the congestion as long as 500 meters will be short, entered the congested area. It took the person to get out of the congested section of 500 meters as long as 25 minutes because of too many vehicles.
Another story is: a person saw the display of “Link A travel time=30 minutes” and assuming that link A takes longer time, selected an alternate route of the target route of traffic information and it took the person 25 minutes to get through. On the link A, only the congested section near the intersection was time-consuming (25 minutes) wile the remaining sections required only five minutes to pass through. Using the road in dotted lines in the target route area displayed on a car navigation system could take only seven minutes to pass through.
As shown in FIG. 42, in case a graph where the vertical axis represents the number of states of traffic information which can be represented (traffic information resolution) and the horizontal axis represents the position (or section) resolution is used to arrange the traffic information, the link travel time has a lower position resolution while it has a higher traffic representation resolution. The congestion information has a lower traffic representation resolution while it has a higher position resolution.
In the current congestion information and link travel time information, an intermediate representation shown in FIG. 42 by circle is not available.
The traffic information in this circle can be collected. In the case of a probe car which collects data from vehicles running on the road, it is possible to collect information at each level in the circle in the center facility. For example, in case a vehicle speed is measured per 300 meters in units of 3 km/h up to 120 km/h, the position resolution is 200 m and the state number resolution is 40. Original information prior to editing collected via an existing sensor is similar traffic information at an intermediate level, although there are variations in the information due to sensor density.
Ideally, a traffic information representation method is preferable which can arbitrarily change both the position resolution and traffic information resolution in line with the source data.
<Problem 2 of the Current Traffic Information>
In the current traffic information provision system, the position resolution and traffic representation resolution are fixed. In case the data volume is huge, the transmission path capacity is exceeded as shown in FIG. 43(a). In this case, the data in excess of the transmission path capacity is lost and the data is not transmitted to the receiving party, however important the data may be.
Ideally, as shown in FIG. 43(b), it is desirable that the data in excess be not lost when the data volume is about to exceed the transmission path capacity and the resolution of data be made “coarse” in ascending order of importance so as to reduce the overall data volume.
As shown in FIG. 44(a), while the transmission path capacity is large enough, the traffic information is represented by a high position resolution and traffic representation resolution. When the information volume has increased near the transmission path capacity, as shown in FIG. 44(b), it is desirable to reduce the position resolution concerning the information on a route whose importance is low, reduce the traffic representation resolution concerning the information on a route distant from the information provision point, or reduce the position resolution and traffic representation resolution concerning the prediction information on far future in order to keep displaying the information on an immediately close route of importance in a high resolution.
<Problem 3 of the Current Traffic Information>
The current traffic information representation form is not fit for representation of traffic prediction information.
Various approaches of traffic prediction have been developed such as a simulation method. With the future development of traffic information providers, services to provide traffic prediction information are expected to grow.
However, the current traffic information provides only the data showing the “increase/decrease trend” as prediction information. An attempt to transmit the prediction information of congestion in the current traffic information representation form results in a proportional increase in the data volume corresponding to the number of prediction time zones. Concerning the congestion state, there are many cases where congestion occurs in a time zone and in the next time zone also. Thus data is transmitted in a duplicated fashion, which is inefficient.